A new reliable cellular automaon(CA) model designed to account for stochasticity in traffic flow induced by heterogeneity in driving behavior is presented.The proposed model differs from most existing CA models in tha...A new reliable cellular automaon(CA) model designed to account for stochasticity in traffic flow induced by heterogeneity in driving behavior is presented.The proposed model differs from most existing CA models in that this new model focuses on describing traffic phenomena by coding into its rules the key idea that a vehicle's moving state is directly determined by a driver stepping on the accelerator or on the brake(the vehicle's acceleration).Acceleration obeys a deformed continuous distribution function when considering the heterogeneity in driving behavior and the safe distance, rather than equaling a fixed acceleration value with a probability, as is the rule in many existing CA models.Simulation results show that the new proposed model is capable of reproducing empirical findings in real traffic system.Moreover, this new model makes it possible to implement in-depth analysis of correlations between a vehicle's state parameters.展开更多
Human settlements are embedded in traffic networks with hierarchical structures. In order to understand the spreading mechanism of infectious diseases and deploy control measures, the susceptible-infected-removed spre...Human settlements are embedded in traffic networks with hierarchical structures. In order to understand the spreading mechanism of infectious diseases and deploy control measures, the susceptible-infected-removed spreading process is studied with agents moving globally on the hierarchical geographic network, taking into account agents’ preference for node layers and memory of initial nodes. We investigate the spreading behavior in the case of global infection under different scenarios, including different directions of human flow, different locations of infection source, and different moving behaviors of agents between layers. Based on the above-mentioned analysis, we propose screening strategies based on layer rank and moving distance, and compare their effects on delaying epidemic spreading. We find that in the case of global infection,infection spreads faster in high layers than in low layers, and early infection in high layers and moving to high layers both accelerate epidemic spreading. Travels of high-layer and low-layer residents have different effects on accelerating epidemic spreading, and moving between high and low layers increases the peak value of new infected cases more than moving in the same layer or between adjacent layers. Infection in intermediate nodes enhances the effects of moving of low-layer residents more than the moving of high-layer residents on accelerating epidemic spreading. For screening measures, improving the success rate is more effective on delaying epidemic spreading than expanding the screening range. With the same number of moves screened, screening moves into or out of high-layer nodes combined with screening moves between subnetworks has better results than only screening moves into or out of high-layer nodes, and screening long-distance moves has the worst results when the screening range is small, but it achieves the best results in reducing the peak value of new infected cases when the screening range is large enough. This study probes into the spreading process and control measures under different scenarios on the hierarchical geographical network, and is of great significance for epidemic control in the real world.展开更多
Pre-warning plays an important role in emergency handling, especially in urban areas with high population density like Beijing. Knowing the information dissemination mechanisms clearly could help us reduce losses and ...Pre-warning plays an important role in emergency handling, especially in urban areas with high population density like Beijing. Knowing the information dissemination mechanisms clearly could help us reduce losses and ensure the safety of human beings during emergencies. In this paper, we propose the models of pre-warning information dissemination via five classical media based on actual pre-warning issue processes, including television, radio, short message service (SMS), electronic screens, and online social networks. The population coverage ability and dissemination efficiency at different issue time of these five issue channels are analyzed by simulation methods, and their advantages and disadvantages are compared by radar graphs. Results show that SMS is the most appropriate way to issue long-term pre-warning for its large population coverage, but it is not suitable for issuing urgent warnings to large population because of the limitation of telecom company's issue ability. TV shows the best performance to combine the dissemination speed and range, and the performance of radio and electronic screens are not as satisfactory as the others. In addition, online social networks might become one of the most promising communication method for its potential in further diffusion. These models and results could help us make pre-warning issue plans and provide guidance for future construction of information diffusion systems, thus reducing injuries, deaths, and other losses under different emergencies.展开更多
In complex networks,identifying influential spreader is of great significance for improving the reliability of networks and ensuring the safe and effective operation of networks.Nowadays,it is widely used in power net...In complex networks,identifying influential spreader is of great significance for improving the reliability of networks and ensuring the safe and effective operation of networks.Nowadays,it is widely used in power networks,aviation networks,computer networks,and social networks,and so on.Traditional centrality methods mainly include degree centrality,closeness centrality,betweenness centrality,eigenvector centrality,k-shell,etc.However,single centrality method is onesided and inaccurate,and sometimes many nodes have the same centrality value,namely the same ranking result,which makes it difficult to distinguish between nodes.According to several classical methods of identifying influential nodes,in this paper we propose a novel method that is more full-scaled and universally applicable.Taken into account in this method are several aspects of node’s properties,including local topological characteristics,central location of nodes,propagation characteristics,and properties of neighbor nodes.In view of the idea of the multi-attribute decision-making,we regard the basic centrality method as node’s attribute and use the entropy weight method to weigh different attributes,and obtain node’s combined centrality.Then,the combined centrality is applied to the gravity law to comprehensively identify influential nodes in networks.Finally,the classical susceptible-infected-recovered(SIR)model is used to simulate the epidemic spreading in six real-society networks.Our proposed method not only considers the four topological properties of nodes,but also emphasizes the influence of neighbor nodes from the aspect of gravity.It is proved that the new method can effectively overcome the disadvantages of single centrality method and increase the accuracy of identifying influential nodes,which is of great significance for monitoring and controlling the complex networks.展开更多
In most situations,staircase is the only egress to evacuate from high-rise buildings.The merging flow on the stair landing has a great influence on the evacuation efficiency.In this paper,we develop an improved cellul...In most situations,staircase is the only egress to evacuate from high-rise buildings.The merging flow on the stair landing has a great influence on the evacuation efficiency.In this paper,we develop an improved cellular automaton model to describe the merging behavior,and the model is validated by a series of real experiments.It is found that the flow rate of simulation results is similar to the drills,which means that the improved model is reasonable and can be used to describe the merging behavior on stairs.Furthermore,some scenarios with different door locations and building floor numbers are simulated by the model.The results show that(i)the best door location is next to the upward staircase;(ii)the total evacuation time and the building floor number are linearly related to each other;(iii)the pedestrians on upper floors have a negative influence on the evacuation flow rate.展开更多
Individuals’ preventive measures,as an effective way to suppress epidemic transmission and to protect themselves from infection,have attracted much academic concern,especially during the COVID-19 pandemic.In this pap...Individuals’ preventive measures,as an effective way to suppress epidemic transmission and to protect themselves from infection,have attracted much academic concern,especially during the COVID-19 pandemic.In this paper,a reinforcement learning-based model is proposed to explore individuals’ effective preventive measures against epidemics.Through extensive simulations,we find that the cost of preventive measures influences the epidemic transmission process significantly.The infection scale increases as the cost of preventive measures grows,which means that the government needs to provide preventive measures with low cost to suppress the epidemic transmission.In addition,the effective preventive measures vary from individual to individual according to the social contacts.Individuals who contact with others frequently in daily life are highly recommended to take strict preventive measures to protect themselves from infection,while those who have little social contacts do not need to take any measures considering the inevitable cost.Our research contributes to exploring the effective measures for individuals,which can provide the government and individuals useful suggestions in response to epidemics.展开更多
Large metro transfer stations have been widely constructed in China,among which the double-island station faces the serious fire safety issues owing to its large passenger flow.In this paper,simulation cases were carr...Large metro transfer stations have been widely constructed in China,among which the double-island station faces the serious fire safety issues owing to its large passenger flow.In this paper,simulation cases were carried out to investigate the effectiveness of different ventilation modes by jointly operating tunnel ventilation fan(TVF)and platform screen doors(PSD)under two typical fire scenarios in the platform.The numerical model was established by Fire Dynamics Simulator software and verified via reduced-scale model experiments.The results indicate that the TVF mode of supplying at the end near fire and exhausting at the other end is superior to that of exhausting at both ends.Besides,activating more PSD and TVF on the both sides of platform will restrict smoke in one end to the greater extent.During a fire in the middle of the platform,opening all PSD near tunnel-2 and TVF in tunnel-2 and tunnel-3 is the most appropriate mode.While during a fire at the left end of the platform,activating all PSD and TVF on both sides is the optimal operation mode.The conclusions can provide guidance for smoke control design and on-site emergency ventilation operation in double-island platform fire.展开更多
As an emerging technology,blockchain provides a range of advantages,such as decentralized and transparent data storage,secure access control,and enhanced data traceability.However,it is rarely applied in the field of ...As an emerging technology,blockchain provides a range of advantages,such as decentralized and transparent data storage,secure access control,and enhanced data traceability.However,it is rarely applied in the field of public safety.This paper presents an in-depth survey of blockchain technology,focusing on its potential applications and implications within the field of public safety research.We explore the practical needs of multi-party data collaboration in emergency management and discusses the applicability and value of blockchain technology in this context.Additionally,this paper introduces and compares several popular blockchain platforms.By providing a comprehensive examination of blockchain technology and its potential benefits for public safety,this paper seeks to enhance understanding of the technology’s capabilities,encourage further research,and inspire innovation in this domain.展开更多
Earthquakes are major catastrophes that cause great life and economic losses to human society and environment.This paper reviews and synthesizes relevant studies,drawing from a systematic examination of 4229 articles ...Earthquakes are major catastrophes that cause great life and economic losses to human society and environment.This paper reviews and synthesizes relevant studies,drawing from a systematic examination of 4229 articles from the Web of Science core collection(1982-2023).Employing the CiteSpace visualization and analysis tool,current research and emerging trends in seismic risk assessment are discussed and analyzed.This paper provides a holistic overview of principal contributions,knowledge sources,interdisciplinary characteristics,and principal research topics in this field.Additionally,we propose key technologies that are in urgent need of enhancement,including data availability,quantity and quality of data,interpretability of machine learning models,perfor-mance improvement of machine learning methods and application of foundation models,as well as real-time risk assessment techniques.These insights support both theoretical understanding and practical applications of seismic risk assessment and damage analysis.展开更多
基金Project supported by the National Key Research and Development Program of China(Grant No.2018YFC0809900)the National Natural Science Foundation of China(Grant Nos.71774093 and 71473146)
文摘A new reliable cellular automaon(CA) model designed to account for stochasticity in traffic flow induced by heterogeneity in driving behavior is presented.The proposed model differs from most existing CA models in that this new model focuses on describing traffic phenomena by coding into its rules the key idea that a vehicle's moving state is directly determined by a driver stepping on the accelerator or on the brake(the vehicle's acceleration).Acceleration obeys a deformed continuous distribution function when considering the heterogeneity in driving behavior and the safe distance, rather than equaling a fixed acceleration value with a probability, as is the rule in many existing CA models.Simulation results show that the new proposed model is capable of reproducing empirical findings in real traffic system.Moreover, this new model makes it possible to implement in-depth analysis of correlations between a vehicle's state parameters.
基金Project supported by the National Key R&D Program of China(Grant No.2018YFF0301005)the National Natural Science Foundation of China(Grant Nos.71673161 and 71790613)the Collaborative Innovation Center of Public Safety,China
文摘Human settlements are embedded in traffic networks with hierarchical structures. In order to understand the spreading mechanism of infectious diseases and deploy control measures, the susceptible-infected-removed spreading process is studied with agents moving globally on the hierarchical geographic network, taking into account agents’ preference for node layers and memory of initial nodes. We investigate the spreading behavior in the case of global infection under different scenarios, including different directions of human flow, different locations of infection source, and different moving behaviors of agents between layers. Based on the above-mentioned analysis, we propose screening strategies based on layer rank and moving distance, and compare their effects on delaying epidemic spreading. We find that in the case of global infection,infection spreads faster in high layers than in low layers, and early infection in high layers and moving to high layers both accelerate epidemic spreading. Travels of high-layer and low-layer residents have different effects on accelerating epidemic spreading, and moving between high and low layers increases the peak value of new infected cases more than moving in the same layer or between adjacent layers. Infection in intermediate nodes enhances the effects of moving of low-layer residents more than the moving of high-layer residents on accelerating epidemic spreading. For screening measures, improving the success rate is more effective on delaying epidemic spreading than expanding the screening range. With the same number of moves screened, screening moves into or out of high-layer nodes combined with screening moves between subnetworks has better results than only screening moves into or out of high-layer nodes, and screening long-distance moves has the worst results when the screening range is small, but it achieves the best results in reducing the peak value of new infected cases when the screening range is large enough. This study probes into the spreading process and control measures under different scenarios on the hierarchical geographical network, and is of great significance for epidemic control in the real world.
基金Project supported by the Science Fund from the Ministry of Science and Technology of China(Grant No.2018YFC0807000).
文摘Pre-warning plays an important role in emergency handling, especially in urban areas with high population density like Beijing. Knowing the information dissemination mechanisms clearly could help us reduce losses and ensure the safety of human beings during emergencies. In this paper, we propose the models of pre-warning information dissemination via five classical media based on actual pre-warning issue processes, including television, radio, short message service (SMS), electronic screens, and online social networks. The population coverage ability and dissemination efficiency at different issue time of these five issue channels are analyzed by simulation methods, and their advantages and disadvantages are compared by radar graphs. Results show that SMS is the most appropriate way to issue long-term pre-warning for its large population coverage, but it is not suitable for issuing urgent warnings to large population because of the limitation of telecom company's issue ability. TV shows the best performance to combine the dissemination speed and range, and the performance of radio and electronic screens are not as satisfactory as the others. In addition, online social networks might become one of the most promising communication method for its potential in further diffusion. These models and results could help us make pre-warning issue plans and provide guidance for future construction of information diffusion systems, thus reducing injuries, deaths, and other losses under different emergencies.
基金Project support by the National Key Research and Development Program of China(Grant No.2018YFF0301000)the National Natural Science Foundation of China(Grant Nos.71673161 and 71790613)。
文摘In complex networks,identifying influential spreader is of great significance for improving the reliability of networks and ensuring the safe and effective operation of networks.Nowadays,it is widely used in power networks,aviation networks,computer networks,and social networks,and so on.Traditional centrality methods mainly include degree centrality,closeness centrality,betweenness centrality,eigenvector centrality,k-shell,etc.However,single centrality method is onesided and inaccurate,and sometimes many nodes have the same centrality value,namely the same ranking result,which makes it difficult to distinguish between nodes.According to several classical methods of identifying influential nodes,in this paper we propose a novel method that is more full-scaled and universally applicable.Taken into account in this method are several aspects of node’s properties,including local topological characteristics,central location of nodes,propagation characteristics,and properties of neighbor nodes.In view of the idea of the multi-attribute decision-making,we regard the basic centrality method as node’s attribute and use the entropy weight method to weigh different attributes,and obtain node’s combined centrality.Then,the combined centrality is applied to the gravity law to comprehensively identify influential nodes in networks.Finally,the classical susceptible-infected-recovered(SIR)model is used to simulate the epidemic spreading in six real-society networks.Our proposed method not only considers the four topological properties of nodes,but also emphasizes the influence of neighbor nodes from the aspect of gravity.It is proved that the new method can effectively overcome the disadvantages of single centrality method and increase the accuracy of identifying influential nodes,which is of great significance for monitoring and controlling the complex networks.
基金Project supported by the National Key Research and Development Program of China(Grant Nos.2017YFC0803300 and 2017YFC0820400)the National Natural Science Foundation of China(Grant No.71673163)
文摘In most situations,staircase is the only egress to evacuate from high-rise buildings.The merging flow on the stair landing has a great influence on the evacuation efficiency.In this paper,we develop an improved cellular automaton model to describe the merging behavior,and the model is validated by a series of real experiments.It is found that the flow rate of simulation results is similar to the drills,which means that the improved model is reasonable and can be used to describe the merging behavior on stairs.Furthermore,some scenarios with different door locations and building floor numbers are simulated by the model.The results show that(i)the best door location is next to the upward staircase;(ii)the total evacuation time and the building floor number are linearly related to each other;(iii)the pedestrians on upper floors have a negative influence on the evacuation flow rate.
基金Project supported by the National Key Technology Research and Development Program of China(Grant No.2018YFF0301000)the National Natural Science Foundation of China(Grant Nos.71673161 and 71790613)。
文摘Individuals’ preventive measures,as an effective way to suppress epidemic transmission and to protect themselves from infection,have attracted much academic concern,especially during the COVID-19 pandemic.In this paper,a reinforcement learning-based model is proposed to explore individuals’ effective preventive measures against epidemics.Through extensive simulations,we find that the cost of preventive measures influences the epidemic transmission process significantly.The infection scale increases as the cost of preventive measures grows,which means that the government needs to provide preventive measures with low cost to suppress the epidemic transmission.In addition,the effective preventive measures vary from individual to individual according to the social contacts.Individuals who contact with others frequently in daily life are highly recommended to take strict preventive measures to protect themselves from infection,while those who have little social contacts do not need to take any measures considering the inevitable cost.Our research contributes to exploring the effective measures for individuals,which can provide the government and individuals useful suggestions in response to epidemics.
基金supported by the National Natural Science Foundation of China(51674152,71790613,51906123)the National Outstanding Youth Science Foundation(51425404).
文摘Large metro transfer stations have been widely constructed in China,among which the double-island station faces the serious fire safety issues owing to its large passenger flow.In this paper,simulation cases were carried out to investigate the effectiveness of different ventilation modes by jointly operating tunnel ventilation fan(TVF)and platform screen doors(PSD)under two typical fire scenarios in the platform.The numerical model was established by Fire Dynamics Simulator software and verified via reduced-scale model experiments.The results indicate that the TVF mode of supplying at the end near fire and exhausting at the other end is superior to that of exhausting at both ends.Besides,activating more PSD and TVF on the both sides of platform will restrict smoke in one end to the greater extent.During a fire in the middle of the platform,opening all PSD near tunnel-2 and TVF in tunnel-2 and tunnel-3 is the most appropriate mode.While during a fire at the left end of the platform,activating all PSD and TVF on both sides is the optimal operation mode.The conclusions can provide guidance for smoke control design and on-site emergency ventilation operation in double-island platform fire.
基金Funded by National Key R&D Program of China(No.2022YFC2602400)National Natural Science Foundation of China(No.72174102,No.72334003)High-tech Discipline Construction Fundings for Universities in Beijing(Safety Science and Engineering).
文摘As an emerging technology,blockchain provides a range of advantages,such as decentralized and transparent data storage,secure access control,and enhanced data traceability.However,it is rarely applied in the field of public safety.This paper presents an in-depth survey of blockchain technology,focusing on its potential applications and implications within the field of public safety research.We explore the practical needs of multi-party data collaboration in emergency management and discusses the applicability and value of blockchain technology in this context.Additionally,this paper introduces and compares several popular blockchain platforms.By providing a comprehensive examination of blockchain technology and its potential benefits for public safety,this paper seeks to enhance understanding of the technology’s capabilities,encourage further research,and inspire innovation in this domain.
基金Funded by National Natural Science Foundation of China(No.72174102,No.72334003,No.72174099)Major Consulting Project of Chinese Academy of Engineering(No.2024-XBZD-21)High-tech Discipline Construction Fundings for Universities in Beijing(Safety Science and Engineering).
文摘Earthquakes are major catastrophes that cause great life and economic losses to human society and environment.This paper reviews and synthesizes relevant studies,drawing from a systematic examination of 4229 articles from the Web of Science core collection(1982-2023).Employing the CiteSpace visualization and analysis tool,current research and emerging trends in seismic risk assessment are discussed and analyzed.This paper provides a holistic overview of principal contributions,knowledge sources,interdisciplinary characteristics,and principal research topics in this field.Additionally,we propose key technologies that are in urgent need of enhancement,including data availability,quantity and quality of data,interpretability of machine learning models,perfor-mance improvement of machine learning methods and application of foundation models,as well as real-time risk assessment techniques.These insights support both theoretical understanding and practical applications of seismic risk assessment and damage analysis.
